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The importance of assessing the impact of climate risk on financial services firms cannot be overstated. In a recent speech, the U.N.'s climate chief warned that governments, business leaders and development banks have only two years to take action to avert far worse climate change[1]. Spurred by warnings like this, as well as regulatory and reputational pressures, financial services firms such as banks, pension funds, investment managers and insurance groups have been focusing on tackling climate risk management and disclosure requirements.
Climate risk disclosure requirements fall into two main categories: transition risk and physical risk.
- Transition Risks require firms to identify the impact of the move to a low-carbon economy, whereas physical risk measures the impact of climate hazards such as wildfire, cyclones, extreme heat/cold, sea level changes and floods.
- Physical Risk reporting and projections of climate hazards need to be propagated through various transmission channels to assess the financial impact of climate hazards to the firm. These channels can include the impact of climate hazards to the replacement cost of assets or facilities owned by the firm, as well as by companies that transact with the firm. It becomes necessary to bring together geospatial climate data, climate scenarios and geospatial asset data for companies a firm is exposed to, together with data on a firm's exposure to various obligors. To do this correctly, it's crucial to rely on credible climate data at a suitable level of granularity and often with global coverage.
As a major provider of financial risk management software, SS&C Algorithmics aims to deliver market-leading climate risk solutions to clients with two main objectives:
- Ensure the solution incorporates advanced research findings and best practices dictated by international organizations and supervisory authorities, and,
- Integrate climate risk quantification into a production-level risk management framework to assess and analyze risks holistically.
SS&C Algorithmics is introducing a strategic partnership with Riskthinking.AI, a data and analytics provider dedicated to supplying science-based, mathematically-sound tools to institutions seeking to measure and manage climate financial risk. It is the leading physical and climate data supplier to Bloomberg LLP and the exclusive provider for the flood data being used by Canadian financial institutions to complete the Standardized Climate Scenario Exercise mandated by OSFI.
“Today, on the heels of Algorithmics’ 35th birthday, which I remember like it was yesterday, I have the pleasure of once again working with the team to help financial firms assess climate risk exposure. We have come full circle," said the founder and CEO of Riskthinking.AI, Ron Dembo.
“Much of the world's portfolios are linked to influential financial indexes such as the S&P 500 or MSCI1000. But, with climate change in full swing, these indexes are mispriced and need to properly reflect the complexities of the transition risks and physical risks embodied in their constituent companies. Our partnership with SS&C Algorithmics will bring critical data to firms to help them assess climate risk exposure and simulate the possible impact climate physical risk might have on firms' portfolios,” shares Dembo.
Riskthinking.AI provides a comprehensive data source of physical assets of over 13,000 parent companies and their 300,000 subsidiaries and provides climate projections across every area of the planet. The datasets cover trillions of data points and petabytes of data.
Figure 1. Climate and asset data are geospatially aligned to hexagonal grids over the globe for a bottom-up physical risk analysis. Source: Riskthinking.AI.
With the launch a new solution, SS&C Physical Risk Exposure Analytics, powered by Riskthinking.AI, SS&C clients can now access data and corresponding climate risk scores to determine the full physical risk exposure of the firms they invest in based on the location of their physical assets globally. Having this information available will enable fund managers and corporate lenders to manage the physical risk concentration in their portfolios much more effectively than before.
The climate risk scores can be calculated at various levels of granularity (asset location, company, sector, sovereignty), for any time horizon decades into the future, and be analyzed together with non-climate risk metrics within the SS&C Algorithmics dashboards. Assessing the vulnerability of firms in the portfolio to future climate conditions becomes crucial for determining whether long-term relationships are at risk of being compromised.
Contact us for a sample RiskThinking.AI physical risk exposure report.
[1] https://www.reuters.com/world/un-climate-chief-says-two-years-save-planet-2024-04-10/
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